Search results for: source identification

Authors: Anjanna Matta, P. A. L. Narayana

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An investigation has been presented to analyze the effect of internal heat source on the onset of Hadley-Prats flow in a horizontal fluid saturated porous medium. We examine a better understanding of the combined influence of the heat source and mass flow effect by using linear stability analysis. The resultant eigenvalue problem is solved by using shooting and Runga-Kutta methods for evaluate critical thermal Rayleight number with respect to various flow governing parameters. It is identified that the flow is switch from stabilizing to destabilizing as the horizontal thermal Rayleigh number is enhanced. The heat source and mass flow increases resulting a stronger destabilizing effect.

Keywords: linear stability analysis, heat source, porous medium, mass flow

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Authors: Mehran Nasiri, Ardeshir Poornemat

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The aim of this study was to investigate the current and ideal situations of the process of talent identification in Iranian football from the point of view of Iranian instructors of the Asian Football Confederation (AFC). This research was a descriptive-analytical study; in data collection phase a questionnaire was used, whose face validity was confirmed by experts of Physical Education and Sports Science. The reliability of questionnaire was estimated through the use of Cronbach's alpha method (0.91). This study involved 122 participants of Iranian instructors of the AFC who were selected based on stratified random sampling method. Descriptive statistics were used to describe the variables and inferential statistics (Chi-square) were used to test the hypotheses of the study at significant level (p ≤ 0.05). The results of Chi-square test related to the point of view of Iranian instructors of the AFC showed that the grass-roots scientific method was the best way to identify football players (0.001), less than 10 years old were the best ages for talent identification (0.001), the Football Federation was revealed to be the most important organization in talent identification (0.002), clubs were shown to be the most important institution in developing talents (0.001), trained scouts of Football Federation were demonstrated to be the best and most appropriate group for talent identification (0.001), and being referred by the football academy coaches was shown to be the best way to attract talented football players in Iran (0.001). It was also found that there was a huge difference between the current and ideal situation of the process of talent identification in Iranian football from the point of view of Iranian instructors of the AFC. Hence, it is recommended that the policy makers of talent identification for Iranian football provide a comprehensive, clear and systematic model of talent identification and development processes for the clubs and football teams, so that the talent identification process helps to nurture football talents more efficiently.

Keywords: current situation, talent finding, ideal situation, instructors (AFC)

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Authors: Abdulkader Helwan

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Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

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Authors: Maha Alaoui Ismaili, Bouchta Saidi, Mohamed Zahar, Abed Hamama

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112 lactic isolates were obtained from 15 samples of camel raw milk produced in Laayoune Boujdour Sakia-El Hamra region (South of Morocco). The main objective was the identification of species of lactic flora belonging to Lactococcus, Lactobacillus and Leuconostoc. Data obtained showed predominance of cocci among lactic isolates (86.6%) while lactic rods represented only 13.4%. With regard to genera identified, Enterococcus was the mostly found out (53.57%), followed by Lactococcus (28.57%), Lactobacillus (13.4%) and Leuconostoc (4.4 %). Identification of the lactic isolates according to their morphological, physiological, and biochemical characteristics led to differentiating 11 species with Lactococcus lactis ssp lactis biovar diacetylactis being the mostly encountered (24.1%) followed by Lactobacillus brevis (3.57%), Lactobacillus plantarum (3.57%), Lactobacillus delbrueckii subsp lactis (3.57%) and Lactococcus lactis subsp cremoris (2.67%).

Keywords: raw camel milk, south of morocco, lactic acid bacteria, identification

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Authors: Çiğdem Sezer, Aksem Aksoy, Leyla Vatansever

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This study has been done for the purpose of evaluation of public health and identifying of enterotoxigenic Staphyloccocus aureus in kitchen of catering. In the kitchen of catering, samples have been taken by swabs from surface of equipments which are in the salad section, meat section and bakery section. Samples have been investigated with classical cultural methods in terms of Staphyloccocus aureus. Therefore, as a 10x10 cm area was identified (salad, cutting and chopping surfaces, knives, meat grinder, meat chopping surface) samples have been taken with sterile swabs with helping FTS from this area. In total, 50 samples were obtained. In aseptic conditions, Baird-Parker agar (with egg yolk tellurite) surface was seeded with swabs. After 24-48 hours of incubation at 37°C, the black colonies with 1-1.5 mm diameter and which are surrounded by a zone indicating lecithinase activity were identified as S. aureus after applying Gram staining, catalase, coagulase, glucose and mannitol fermentation and termonuclease tests. Genotypic characterization (Staphylococcus genus and S.aureus species spesific) of isolates was performed by PCR. The ELISA test was applied to the isolates for the identification of staphylococcal enterotoxins (SET) A, B, C, D, E in bacterial cultures. Measurements were taken at 450 nm in an ELISA reader using an Ridascreen-Total set ELISA test kit (r-biopharm R4105-Enterotoxin A, B, C, D, E). The results were calculated according to the manufacturer’s instructions. A total of 50 samples of 97 S. aureus was isolated. This number has been identified as 60 with PCR analysis. According to ELISA test, only 1 of 60 isolates were found to be enterotoxigenic. Enterotoxigenic strains were identified from the surface of salad chopping and cutting. In the kitchen of catering, S. aureus identification indicates a significant source of contamination. Especially, in raw consumed salad preparation phase of contamination is very important. This food can be a potential source of food-borne poisoning their terms, and they pose a significant risk to consumers have been identified.

Keywords: Staphylococcus aureus, enterotoxin, catering, kitchen, health

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Authors: A. A. M. A. S. S. Perera, L. A. Ranasinghe, T. K. H. Nimeshika, D. M. Dhanushka Dissanayake, Namalie Walgampaya

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Nowadays, skin fungal diseases are mostly found in people of tropical countries like Sri Lanka. A skin fungal disease is a particular kind of illness caused by fungus. These diseases have various dangerous effects on the skin and keep on spreading over time. It becomes important to identify these diseases at their initial stage to control it from spreading. This paper presents an automated skin fungal disease identification system implemented to speed up the diagnosis process by identifying skin fungal infections in digital images. An image of the diseased skin lesion is acquired and a comprehensive computer vision and image processing scheme is used to process the image for the disease identification. This includes colour analysis using RGB and HSV colour models, texture classification using Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix and Local Binary Pattern, Object detection, Shape Identification and many more. This paper presents the approach and its outcome for identification of four most common skin fungal infections, namely, Tinea Corporis, Sporotrichosis, Malassezia and Onychomycosis. The main intention of this research is to provide an automated skin fungal disease identification system that increase the diagnostic quality, shorten the time-to-diagnosis and improve the efficiency of detection and successful treatment for skin fungal diseases.

Keywords: Circularity Index, Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix, Local Binary Pattern, Object detection, Ring Detection, Shape Identification

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Authors: Terence Soule, Tami Al Ghamdi

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To study how to transfer knowledge from multiple source problems to the target problem, we modeled the Transfer Learning (TL) process using Genetic Algorithms as the model solver. TL is the process that aims to transfer learned data from one problem to another problem. The TL process aims to help Machine Learning (ML) algorithms find a solution to the problems. The Genetic Algorithms (GA) give researchers access to information that we have about how the old problem is solved. In this paper, we have five different source problems, and we transfer the knowledge to the target problem. We studied different scenarios of the target problem. The results showed combined knowledge from multiple source problems improves the GA performance. Also, the process of combining knowledge from several problems results in promoting diversity of the transferred population.

Keywords: transfer learning, genetic algorithm, evolutionary computation, source and target

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Authors: N. Jinesh, K. Shankar

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This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally.

Keywords: inverse problem, particle swarm optimization, PZT patches, structural identification

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Authors: Eric Bonetto, Anthony Piermatteo, Fabien Girandola, Gregory Lo Monaco

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The present contribution focuses on the effect of the structure of social representations on group identification. A social representation (SR) is defined as an organized and structured set of cognitions, produced and shared by members of a same group about a same social object. Within this framework, the central core theory establishes a structural distinction between central cognitions – or 'core' – and peripheral ones: the former are theoretically considered as more connected than the later to group members’ social identity and may play a greater role in SRs’ ability to allow group identification by means of a common vision of the object of representation. Indeed, the central core provides a reference point for the in-group as it constitutes a consensual vision that gives meaning to a social object particularly important to individuals and to the group. However, while numerous contributions clearly refer to the underlying role of SRs in group identification, there are only few empirical evidences of this aspect. Thus, we hypothesize an effect of the structure of SRs on group identification. More precisely, central cognitions (vs. peripheral ones) will lead to a stronger group identification. In addition, we hypothesize that the refutation of a cognition will lead to a stronger group identification than its activation. The SR mobilized here is that of 'studying' among a population of first-year undergraduate psychology students. Thus, a pretest (N = 82), using an Attribute-Challenge Technique, was designed in order to identify the central and the peripheral cognitions to use in the primings of our main study. The results of this pretest are in line with previous studies. Then, the main study (online; N = 184), using a social priming methodology, was based on a 2 (Structural status of the cognitions belonging to the prime: central vs. peripheral) x 2 (Type of prime: activation vs. refutation) experimental design in order to test our hypotheses. Results revealed, as expected, the main effect of the structure of the SR on group identification. Indeed, central cognitions trigger a higher level of identification than the peripheral ones. However, we observe neither effect of the type of prime, nor interaction effect. These results experimentally demonstrate for the first time the effect of the structure of SRs on group identification and indicate that central cognitions are more connected than peripheral ones to group members’ social identity. These results will be discussed considering the importance of understanding identity as a function of SRs and on their ability to potentially solve the lack of consideration of the definition of the group in Social Representations Theory.

Keywords: group identification, social identity, social representations, structural approach

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Authors: A. Ballard

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The ability to track goods and products en route in the delivery system, in the warehouse, and on the top floor is a huge advantage to shippers and retailers. Recently the emergence of radio frequency identification (RFID) technology has enabled this better than ever before. However, a significant problem exists in that RFID technology depends on the quality of the information stored for each tagged product. Because of the profusion of names for colours, it is very difficult to ascertain that stored values are recognised by all users who view the product visually. This paper reports the findings of a study in which 50 consumers and 50 logistics workers were shown colour swatches and asked to choose the name of the colour from a multiple choice list. They were then asked to match consumer products, including toasters, jumpers, and toothbrushes, with the identifying inventory information available for each one. The findings show that the ability to match colours was significantly stronger with the color swatches than with the consumer products and that while logistics professionals made more frequent correct identification than the consumers, their results were still unsatisfactorily low. Based on these findings, a proposed universal model of colour identification numbers has been developed.

Keywords: consumer preferences, supply chain logistics, radio frequency identification, RFID, colour preference

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Authors: Ayman El Behiry, Rasha Nabil Zahran, Reda Tarabees, Eman Marzouk, Musaad Al-Dubaib

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Mastitis is one of the most economic disease affecting dairy cows worldwide. Its classic diagnosis using bacterial culture and biochemical findings is a difficult and prolonged method. In this research, using of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) permitted identification of different microorganisms with high accuracy and rapidity (only 24 hours for microbial growth and analysis). During the application of MALDI-TOF MS, one hundred twenty strains of Staphylococcus and Streptococcus species isolated from milk of cows affected by clinical and subclinical mastitis were identified, and the results were compared with those obtained by traditional methods as API and VITEK 2 Systems. 37 of totality 39 strains (~95%) of Staphylococcus aureus (S. aureus) were exactly detected by MALDI TOF MS and then confirmed by a nuc-based PCR technique, whereas accurate identification was observed in 100% (50 isolates) of the coagulase negative staphylococci (CNS) and Streptococcus agalactiae (31 isolates). In brief, our results demonstrated that MALDI-TOF MS is a fast and truthful technique which has the capability to replace conventional identification of several bacterial strains usually isolated in clinical laboratories of microbiology.

Keywords: identification, mastitis pathogens, mass spectral, phenotypical

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Authors: Mohamed Adnan Landolsi, Ali F. Almutairi

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The paper addresses the problem of line-of-sight (LOS) vs. non-line-of-sight (NLOS) propagation link identification in ultra-wideband (UWB) wireless networks, which is necessary for improving the accuracy of radiolocation and positioning applications. A LOS/NLOS likelihood hypothesis testing approach is applied based on exploiting distinctive statistical features of the channel impulse response (CIR) using parameters related to the “skewness” of the CIR and its root mean square (RMS) delay spread. A log-normal fit is presented for the probability densities of the CIR parameters. Simulation results show that different environments (residential, office, outdoor, etc.) have measurable differences in their CIR parameters’ statistics, which is then exploited in determining the nature of the propagation channels. Correct LOS/NLOS channel identification rates exceeding 90% are shown to be achievable for most types of environments. Additional improvement is also obtained by combining both CIR skewness and RMS delay statistics.

Keywords: UWB, propagation, LOS, NLOS, identification

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Authors: Feride Eskin Bacaksiz, Aytolan Yildirim

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Practices voluntarily performed by organizations for their employees well-being, create an emotional imperative for employees in accordance with reciprocity norm. Changes in desired course occur in organizational outputs and attitudes towards organization among employees perceiving their organizations as virtuous and supportive. The aim of this study was to examine the effect of organizational virtuousness on performance and organizational identification levels of employees and mediating role of perceived organizational support in this relationship. The data of this descriptive and methodological study were collected from 336 nurses working in a public university hospital in 2015. Participant information form, Organizational Virtuousness, Perceived Organizational Support, Organizational Identification, and Employee Performance scales were used to collect the data. Descriptive, correlative, psychometric analyses and Structural Equation Modeling were performed for the data analysis. Most of the participants were female, under 30 years of age, graduated degrees and staff nurse. Mean scores obtained by the participants from scales were calculated as 3.43(SD=.99) for organizational virtuousness, 2.99 (SD=1.16) for perceived organizational support, 3.18 (SD=1.03) for organizational identification and 3.84 (SD=0.66) for employee performance. It was found that correlation between organizational virtuousness and employee performance regressed from r=0.64 to r=-0.01 and correlation between organizational virtuousness and organizational identification regressed from r=0.55 to r=-0.16 and became statistically non-significant (p < 0.05) via mediating role of perceived organizational support. According to the results, perceived organizational support assumes full mediation on the impact of organizational virtues of employee performance and organizational identification levels. Therefore, organizations, which intend to positively affect employees attitudes towards organization and their performance, should both extend organizational virtuous activities and affect perceptions of employees; whereas, employees should perceive that they are supported by their organization.

Keywords: employee performance, organizational identification, organizational virtuousness, perceived organizational support

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Authors: Parag Nihawan, Ravinder Singh Bhatia, Dinesh Kumar Jain

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Industrial drives are source of serious power quality problems. In this, two typical industrial drives have been dealt with, namely, FOC induction motor drives and DTC induction motor drive. The Z-source inverter is an emerging topology of power electronic converters which is capable of buck boost characteristics. The performances of different control methods based Z-source inverters feeding these industrial drives have been investigated, in this work. The test systems have been modeled and simulated in MATLAB/SIMULINK. The results obtained after carrying out these simulations have been used to draw the conclusions.

Keywords: Z-source inverter, total harmonic distortion, direct torque control, field orientation control

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Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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Authors: Okorowo Cyril Agochi

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The main challenge of present world is to harness the energy source which is environment friendly and ecologically balanced. This need has forced to search for other alternate source of energy. But unfortunately the new alternative energy sources like the solar, hydro, wind etc. require huge economical value and technical power to operate, which seem to be very difficult for the developing countries like Nigeria. In the present moment biogas energy can be one and only reliable, easily available and economically feasible source of alternative and renewable source which can be managed by locally available sources and simple technology for secondary schools, tertiary institution and rural villages. This paper is aimed at boosting the energy generation for developing of rural Nigeria, through Biogas.

Keywords: bio-gas, energy, environment, nigeria, technology

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Authors: Raquel Rossini, Edelvais Caldeira

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The aim of this work is to investigate the motivation for the metaphorical uses of two verb combinations: come out and take over. Drawing from cognitive semantics theories, image schemas and metaphors, it was attempted to demonstrate that: a) the metaphorical senses of both 'come out' and 'take over' extend from both the verbs and the particles central (spatial) senses in such verb combinations; and b) the particles 'out' and 'over' also contribute to the whole meaning of the verb combinations. In order to do so, a random selection of 579 concordance lines for come out and 1,412 for take over was obtained from the Corpus of Contemporary American English – COCA. One of the main procedures adopted in the present work was the establishment of verb and particle central senses. As per the research questions addressed in this study, they are as follows: a) how does the identification of trajector and landmark help reveal patterns that contribute for the identification of the semantic network of these two verb combinations?; b) what is the relationship between the schematic structures attributed to the particles and the metaphorical uses found in empirical data?; and c) what conceptual metaphors underlie the mappings from the source to the target domains? The results demonstrated that not only the lexical verbs come and take, but also the particles out and over play an important whole in the different meanings of come out and take over. Besides, image schemas and conceptual metaphors were found to be helpful in order to establish the motivations for the metaphorical uses of these linguistic structures.

Keywords: cognitive linguistics, English syntax, multi-word verbs, prepositions

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Authors: E. Krasnova, E. Bulgakova, V. Shchemelinin

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The paper deals with acoustic-spectrographic voice identification method in terms of its performance in non-native language speech. Performance evaluation is conducted by comparing the result of the analysis of recordings containing native language speech with recordings that contain foreign language speech. Our research is based on Tajik and Russian speech of Tajik native speakers due to the character of the criminal situation with drug trafficking. We propose a pilot experiment that represents a primary attempt enter the field.

Keywords: speaker identification, acoustic-spectrographic method, non-native speech, performance evaluation

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Authors: B. Mahfoud, A. Bendjaghlouli

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Natural convection is simulated in a truncated cone filled with nanofluid. Inclined and top walls have constant temperature where the heat source is located on the bottom wall of the conical container which is thermally insulated. A finite volume approach is used to solve the governing equations using the SIMPLE algorithm for different parameters such as Rayleigh number, inclination angle of inclined walls of the enclosure and heat source length. The results showed an enhancement in cooling system by using a nanofluid, when conduction regime is assisted. The inclination angle of inclined sidewall and heat source length affect the heat transfer rate and the maximum temperature.

Keywords: heat source, truncated cone, nanofluid, natural convection

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Authors: Degale Desta, Cheng Jian

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The most important factor in identifying a person is their face. Even identical twins have their own distinct faces. As a result, identification and face recognition are needed to tell one person from another. A face recognition system is a verification tool used to establish a person's identity using biometrics. Nowadays, face recognition is a common technique used in a variety of applications, including home security systems, criminal identification, and phone unlock systems. This system is more secure because it only requires a facial image instead of other dependencies like a key or card. Face detection and face identification are the two phases that typically make up a human recognition system.The idea behind designing and creating a face recognition system using deep learning with Azure ML Python's OpenCV is explained in this paper. Face recognition is a task that can be accomplished using deep learning, and given the accuracy of this method, it appears to be a suitable approach. To show how accurate the suggested face recognition system is, experimental results are given in 98.46% accuracy using Fast-RCNN Performance of algorithms under different training conditions.

Keywords: deep learning, face recognition, identification, fast-RCNN

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Authors: Surbhi Mathur, J. M. Vyas

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Although the rapid development of forensic speaker recognition technology has been conducted, there are still many problems to be solved. The biggest problem arises when the cases involving disguised voice samples come across for the purpose of examination and identification. Such type of voice samples of anonymous callers is frequently encountered in crimes involving kidnapping, blackmailing, hoax extortion and many more, where the speaker makes a deliberate effort to manipulate their natural voice in order to conceal their identity due to the fear of being caught. Voice disguise causes serious damage to the natural vocal parameters of the speakers and thus complicates the process of identification. The sole objective of this doctoral project is to find out the possibility of rendering definite opinions in cases involving disguised speech by experimentally determining the effects of different disguise forms on personal identification and percentage rate of speaker recognition for various voice disguise techniques such as raised pitch, lower pitch, increased nasality, covering the mouth, constricting tract, obstacle in mouth etc by analyzing and comparing the amount of phonetic and acoustic variation in of artificial (disguised) and natural sample of an individual, by auditory as well as spectrographic analysis.

Keywords: forensic, speaker recognition, voice, speech, disguise, identification

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Authors: Rebecca Angeles

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This qualitative case study seeks to understand and explain the deployment of radio frequency identification (RFID) systems in two countries (i.e. in Taiwan for the adoption of electric scooters and in Finland for supporting glass bottle recycling) using the 'Technology-Organization-Environment' theoretical framework. This study also seeks to highlight the relevance and importance of pursuing environmental sustainability in firms and in society in general due to the social urgency of the issues involved.

Keywords: environmental sustainability, radio frequency identification, technology-organization-environment framework, RFID system implementation, case study, content analysis

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Authors: Mohammad Asadpour, Gholamreza Razmi, Gholamreza Mohammadi, Abolghasem Naghibi

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Cryptosporidium Spp., protozoan parasites of the phylum Apicomplexa, have a wide spectrum of hosts including humans, domestic animals and wild mammals, birds, reptiles, amphibians and fish. Dairy cattle have been identified in numerous reports as a major source of environmental contamination with this pathogen. In this study, a Polymerase Chain Reaction (PCR), Restriction Fragment Length Polymorphism (RFLP) analysis of the Small-Subunit (SSU) rRNA gene was used to detect and identify Cryptosporidium Spp. in 300 fecal specimens from 1 to 30 days pre-wean calves in 10 farms in Mashhad, Iran. Eighty five (28.3%) and forty five (15%) of the specimens were positive for Cryptosporidium by microscopic and PCR examination respectively. Restriction digestion of the PCR products by VSPI and Ssp1 restriction enzymes and analysis of sequence data revealed the presence of C. parvum, bovine genotype in all isolates. Our findings suggest that cattle can be a source of Cryptosporidial infections for humans and animals in Mashhad area. This is the first published description of Cryptosporidium sub genotyping in Mashhad.

Keywords: cryptosporidium, genotype, dairy calves, 18S rRNA, Mashhad

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Authors: Aditi Chauhan, Neethu S. Mohan

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In the modern era, the advancement and digitalization in technology have taken place during an investigation of crime scene. The rapid enhancement and investigative techniques have changed the mean of identification of suspect. Identification of the person is one of the significant aspects, and personal authentication is the key of security and reliability in society. Since early 90 s, people have relied on comparing handwriting through its class and individual characteristics. But in today’s 21st century we need more reliable means to identify individual through handwriting. An approach employing computer modalities have lately proved itself auspicious enough in exploration of hieroglyphics substantial in investigating the case. Various software’s such as FISH, WRITEON, and PIKASO, CEDAR-FOX SYSTEM identify and verify the associated quantitative measure of the similarity between two samples. The research till date has been confined to identify the authorship of the concerned samples. But prospects associated with the use of computational modalities might help to identify disguised writing, forged handwriting or say altered or modified writing. Considering the applications of such modal, similar work is sure to attract plethora of research in immediate future. It has a promising role in national security too. Documents exchanged among terrorist can also be brought under the radar of surveillance, bringing forth their source of existence.

Keywords: documents, identity, computational system, suspect

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Authors: Fadwa Haraka, Ahmad Elouatouati, Mourad Taha Janan

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In this study, we propose a neural network based method in order to calculate the heat source temperature of isotropic plate with lower surface forced cooling. To validate the proposed model, the heat source temperatures values will be compared to the analytical method -variables separation- and finite element model. The mathematical simulation is done through 3D numerical simulation by COMSOL software considering three different materials: Aluminum, Copper, and Graphite. The proposed method will lead to a formulation of the heat source temperature based on the thermal and geometric properties of the base plate.

Keywords: thermal model, thermal resistance, finite element simulation, neural network

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Authors: Zain Ul Abdin, Mirza Aizaz Asim, Rao Sohail Ahmad Khan, Luqman Amrao, Fiaz Hussain, Hasooba Hira, Saqi Kosar Abbas

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The success of Integrated vector management programmes mainly depends on the correct identification of insect vector species involved in vector borne diseases. Based on molecular data the most important insect species involved as vectors for Zoonotic diseases in Pakistan were identified. The precise and accurate identification of such type of organism is only possible through molecular based techniques like “DNA barcoding”. Morphological species identification in insects at any life stage, is very challenging, therefore, DNA barcoding was used as a tool for rapid and accurate species identification in a wide variety of taxa across the globe and parallel studies revealed that DNA barcoding data can be effectively used in resolving taxonomic ambiguities, detection of cryptic diversity, invasion biology, description of new species etc. A comprehensive survey was carried out for the collection of insects (both adult and immature stages) in district Faisalabad, Pakistan and their DNA was extracted and mitochondrial cytochrome oxidase subunit I (COI-59) barcode sequences was used for molecular identification of immature and adult life stage.This preliminary research work opens new frontiers for developing sustainable insect vectors management programmes for saving lives of mankind from fatal diseases.

Keywords: zoonotic diseases, cytochrome oxidase, and insect vectors, CO1

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Authors: Kais Manai

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The main part of this work focuses on the study of pion/muon separation at low energy using a nuclear Emulsion Cloud Chamber (ECC) made of lead and nuclear emulsion films. The work consists of two parts: particle reconstruction algorithm and a Neural Network that assigns to each reconstructed particle the probability to be a muon or a pion. The pion/muon separation algorithm has been optimized by using a detailed Monte Carlo simulation of the ECC and tested on real data. The algorithm allows to achieve a 60% muon identification efficiency with a pion misidentification smaller than 3%.

Keywords: nuclear emulsion, particle identification, tracking, neural network

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Authors: Md Serajul Islam

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High Dose Rate (HDR) Brachytherapy is used for cancer patients. In our country’s prospect, we are using only cervices and breast cancer treatment by using HDR. The air kerma rate in air at a reference distance of less than a meter from the source is the recommended quantity for the specification of gamma ray source Ir-192 in brachytherapy. The absorbed dose for the patients is directly proportional to the air kerma rate. Therefore the air kerma rate should be determined before the first use of the source on patients by qualified medical physicist who is independent from the source manufacturer. The air kerma rate will then be applied in the calculation of the dose delivered to patients in their planning systems. In practice, high dose rate (HDR) Ir-192 afterloader machines are mostly used in brachytherapy treatment. Currently, HDR-Co-60 increasingly comes into operation too. The essential advantage of the use of Co-60 sources is its longer half-life compared to Ir-192. The use of HDRCo-60 afterloading machines is also quite interesting for developing countries. This work describes the dosimetry at HDR afterloading machines according to the protocols IAEA-TECDOC-1274 (2002) with the nuclides Ir-192 and Co-60. We have used 3 different measurement methods (with a ring chamber, with a solid phantom and in free air and with a well chamber) in dependence of each of the protocols. We have shown that the standard deviations of the measured air kerma rate for the Co-60 source are generally larger than those of the Ir-192 source. The measurements with the well chamber had the lowest deviation from the certificate value. In all protocols and methods, the deviations stood for both nuclides by a maximum of about 1% for Ir-192 and 2.5% for Co-60-Sources respectively.

Keywords: Ir-192 source, cancer, patients, cheap treatment cost

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Authors: Bale Baidi Blaise, Gilles Marckmann, Liman Kaoye, Talaka Dya, Moustapha Bachirou, Gambo Betchewe, Tibi Beda

Abstract:

This work highlights the capabilities of particles swarm optimization (PSO) method to identify parameters of hyperelastic models. The study compares this method with Genetic Algorithm (GA) method, Least Squares (LS) method, Pattern Search Algorithm (PSA) method, Beda-Chevalier (BC) method and the Levenberg-Marquardt (LM) method. Four classic hyperelastic models are used to test the different methods through parameters identification. Then, the study compares the ability of these models to reproduce experimental Treloar data in simple tension, biaxial tension and pure shear.

Keywords: particle swarm optimization, identification, hyperelastic, model

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Authors: Brandon Foggo, Nanpeng Yu

Abstract:

Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: distribution network, machine learning, network topology, phase identification, smart grid

Procedia PDF Downloads 273